Structure preserving splitting integrators for SDEs
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In this talk we will discuss stochastic differential equations, where the solution trajectories are governed by geometric structures as, e.g., energy preservation or dissipation. An efficient strategy for constructing structure preserving integrators is to split the SDE into subsystems which inherit the geometric structure and build a numerical integrator by composition of the exact flows of the subsystems. We apply this approach on SDEs arising in micromagnetism (stochastic Landau-Lifshitz-Gilbert equation) and neuroscience (stochastic Jansen and Rit Neural Mass Model).